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Data X:
115.6 111.3 114.6 137.5 83.7 106.0 123.4 126.5 120.0 141.6 90.5 96.5 113.5 120.1 123.9 144.4 90.8 114.2 138.1 135.0 131.3 144.6 101.7 108.7 135.3 124.3 138.3 158.2 93.5 124.8 154.4 152.8 148.9 170.3 124.8 134.4 154.0 147.9 168.1 175.7 116.7 140.8 164.2 173.8 167.8 166.6 135.1 158.1 151.8 166.7 165.3 187.0 125.2 144.4 181.7 175.9 166.3 181.5 121.8 134.8 162.9
Data Y:
109.7 99.1 86.7 111.4 78.4 76.7 114.2 99.7 94.2 173.5 83.1 88.9 132.0 122.1 105.1 133.7 63.6 112.7 120.5 112.0 126.2 209.2 91.0 116.7 137.6 108.1 136.6 152.3 114.3 120.7 131.8 129.4 187.5 189.5 109.2 158.1 176.2 125.5 155.0 170.3 99.4 139.2 169.6 136.1 168.2 318.6 154.1 161.4 183.4 166.3 203 174.6 124.3 154.4 170.5 169.4 171.1 289.2 145.6 134.4 168.2
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
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# lags (autocorrelation function)
(?)
36
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Chart options
Label y-axis:
Label x-axis:
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) y <- as.ts(y) mylm <- lm(y~x) cbind(mylm$resid) library(lattice) bitmap(file='pic1.png') plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic1a.png') plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic1b.png') plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]') grid() dev.off() bitmap(file='pic1c.png') plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic2.png') hist(mylm$resid,main='Histogram of e[t]') dev.off() bitmap(file='pic3.png') if (par1 > 0) { densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t] bw = ',par1),bw=par1) } else { densityplot(~mylm$resid,col='black',main='Density Plot of e[t]') } dev.off() bitmap(file='pic4.png') qqnorm(mylm$resid,main='QQ plot of e[t]') qqline(mylm$resid) grid() dev.off() if (par2 > 0) { bitmap(file='pic5.png') acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function') grid() dev.off() } summary(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'c',1,TRUE) a<-table.element(a,mylm$coeff[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'b',1,TRUE) a<-table.element(a,mylm$coeff[[2]]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations',header=TRUE) a<-table.element(a,length(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'minimum',header=TRUE) a<-table.element(a,min(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,quantile(mylm$resid,0.25)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,quantile(mylm$resid,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum',header=TRUE) a<-table.element(a,max(mylm$resid)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Summary of computational transaction
Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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